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“Awake” intraoperative functional MRI (ai-fMRI) for mapping the eloquent cortex: Is it possible in awake craniotomy?
Author(s) -
Junfeng Lu,
Han Zhang,
Jinsong Wu,
Chengjun Yao,
Dongxiao Zhuang,
Tianming Qiu,
Wenbin Jia,
Ying Mao,
Liangfu Zhou
Publication year - 2012
Publication title -
neuroimage clinical
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.772
H-Index - 68
ISSN - 2213-1582
DOI - 10.1016/j.nicl.2012.12.002
Subject(s) - awake craniotomy , functional magnetic resonance imaging , eeg fmri , neuroscience , brain mapping , craniotomy , psychology , medicine , electroencephalography , radiology
As a promising noninvasive imaging technique, functional MRI (fMRI) has been extensively adopted as a functional localization procedure for surgical planning. However, the information provided by preoperative fMRI (pre-fMRI) is hampered by the brain deformation that is secondary to surgical procedures. Therefore, intraoperative fMRI (i-fMRI) becomes a potential alternative that can compensate for brain shifts by updating the functional localization information during craniotomy. However, previous i-fMRI studies required that patients be under general anesthesia, preventing the wider application of such a technique as the patients cannot perform tasks unless they are awake. In this study, we propose a new technique that combines awake surgery and i-fMRI, named "awake" i-fMRI (ai-fMRI). We introduced ai-fMRI to the real-time localization of sensorimotor areas during awake craniotomy in seven patients. The results showed that ai-fMRI could successfully detect activations in the bilateral primary sensorimotor areas and supplementary motor areas for all patients, indicating the feasibility of this technique in eloquent area localization. The reliability of ai-fMRI was further validated using intraoperative stimulation mapping (ISM) in two of the seven patients. Comparisons between the pre-fMRI-derived localization result and the ai-fMRI derived result showed that the former was subject to a heavy brain shift and led to incorrect localization, while the latter solved that problem. Additionally, the approaches for the acquisition and processing of the ai-fMRI data were fully illustrated and described. Some practical issues on employing ai-fMRI in awake craniotomy were systemically discussed, and guidelines were provided.

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